Search results for: high resolution satellite image

Authors: Charles Davidson

Abstract:

This paper presents the Stoplight Analysis System of Partnering Organizations Readiness, offering a structured framework to evaluate conflict resolution collaboration feasibility, especially crucial in conflict areas, employing a colour-coded approach and specific assessment points, with implications for more informed decision-making and improved outcomes in peacebuilding initiatives. Derived from at total of 40 years of practical peacebuilding experience from the project’s two researchers as well as interviews of various other peacebuilding actors, this paper introduces the Stoplight Analysis System of Partnering Organizations Readiness, a comprehensive framework designed to facilitate effective collaboration in international/local peacebuilding partnerships by evaluating the readiness of both potential partner organisations and the location of the proposed project. ^The system employs a colour-coded approach, categorising potential partnerships into three distinct indicators: Red (no-go), Yellow (requires further research), and Green (promising, go ahead). Within each category, specific points are identified for assessment, guiding decision-makers in evaluating the feasibility and potential success of collaboration. The Red category signals significant barriers, prompting an immediate stoppage in the consideration of partnership. The Yellow category encourages deeper investigation to determine whether potential issues can be mitigated, while the Green category signifies organisations deemed ready for collaboration. This systematic and structured approach empowers decision-makers to make informed choices, enhancing the likelihood of successful and mutually beneficial partnerships. Methodologically, this paper utilised interviews from peacebuilders from around the globe, scholarly research of extant strategies, and a collaborative review of programming from the project’s two authors from their own time in the field. This method as a formalised model has been employed for the past two years across a litany of partnership considerations, and has been adjusted according to its field experimentation. This research holds significant importance in the field of conflict resolution as it provides a systematic and structured approach to peacebuilding partnership evaluation. In conflict-affected regions, where the dynamics are complex and challenging, the Stoplight Analysis System offers decision-makers a practical tool to assess the readiness of partnering organisations. This approach can enhance the efficiency of conflict resolution efforts by ensuring that resources are directed towards partnerships with a higher likelihood of success, ultimately contributing to more effective and sustainable peacebuilding outcomes.

Keywords: collaboration, conflict resolution, partnerships, peacebuilding

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Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

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Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

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Authors: Andrey Cherdantsev, Mikhail Cherdantsev, Sergey Isaenkov, Dmitriy Markovich

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In annular gas-liquid flow, liquid flows as a film along pipe walls sheared by high-velocity gas stream. Film surface is covered by large-scale disturbance waves which affect pressure drop and heat transfer in the system and are necessary for entrainment of liquid droplets from film surface into the core of gas stream. Disturbance waves are a highly complex and their properties are affected by numerous parameters. One of such aspects is flow development, i.e., change of flow properties with the distance from the inlet. In the present work, this question is studied using brightness-based laser-induced fluorescence (BBLIF) technique. This method enables one to perform simultaneous measurements of local film thickness in large number of points with high sampling frequency. In the present experiments first 50 cm of upward and downward annular flow in a vertical pipe of 11.7 mm i.d. is studied with temporal resolution of 10 kHz and spatial resolution of 0.5 mm. Thus, spatiotemporal evolution of film surface can be investigated, including scenarios of formation, acceleration and coalescence of disturbance waves. The behaviour of disturbance waves' velocity depending on phases flow rates and downstream distance was investigated. Besides measuring the waves properties, the goal of the work was to investigate the interrelation between disturbance waves properties and integral characteristics of the flow such as interfacial shear stress and flow rate of dispersed phase. In particular, it was shown that the initial acceleration of disturbance waves, defined by the value of shear stress, linearly decays with downstream distance. This lack of acceleration which may even lead to deceleration is related to liquid entrainment. Flow rate of disperse phase linearly grows with downstream distance. During entrainment events, liquid is extracted directly from disturbance waves, reducing their mass, area of interaction to the gas shear and, hence, velocity. Passing frequency of disturbance waves at each downstream position was measured automatically with a new algorithm of identification of characteristic lines of individual disturbance waves. Scenarios of coalescence of individual disturbance waves were identified. Transition from initial high-frequency Kelvin-Helmholtz waves appearing at the inlet to highly nonlinear disturbance waves with lower frequency was studied near the inlet using 3D realisation of BBLIF method in the same cylindrical channel and in a rectangular duct with cross-section of 5 mm by 50 mm. It was shown that the initial waves are generally two-dimensional but are promptly broken into localised three-dimensional wavelets. Coalescence of these wavelets leads to formation of quasi two-dimensional disturbance waves. Using cross-correlation analysis, loss and restoration of two-dimensionality of film surface with downstream distance were studied quantitatively. It was shown that all the processes occur closer to the inlet at higher gas velocities.

Keywords: annular flow, disturbance waves, entrainment, flow development

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Authors: Eugen Rusu

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The objective of the work proposed is to perform an analysis of the wave conditions in the Black Sea basin. This is especially focused on the spatial and temporal occurrences and on the dynamics of the most extreme storms in the context of the climate changes. A numerical modelling system, based on the spectral phase averaged wave model SWAN, has been implemented and validated against both in situ measurements and remotely sensed data, all along the sea. Moreover, a successive correction method for the assimilation of the satellite data has been associated with the wave modelling system. This is based on the optimal interpolation of the satellite data. Previous studies show that the process of data assimilation improves considerably the reliability of the results provided by the modelling system. This especially concerns the most sensitive cases from the point of view of the accuracy of the wave predictions, as the extreme storm situations are. Following this numerical approach, it has to be highlighted that the results provided by the wave modelling system above described are in general in line with those provided by some similar wave prediction systems implemented in enclosed or semi-enclosed sea basins. Simulations of this wave modelling system with data assimilation have been performed for the 30-year period 1987-2016. Considering this database, the next step was to analyze the intensity and the dynamics of the higher storms encountered in this period. According to the data resulted from the model simulations, the western side of the sea is considerably more energetic than the rest of the basin. In this western region, regular strong storms provide usually significant wave heights greater than 8m. This may lead to maximum wave heights even greater than 15m. Such regular strong storms may occur several times in one year, usually in the wintertime, or in late autumn, and it can be noticed that their frequency becomes higher in the last decade. As regards the case of the most extreme storms, significant wave heights greater than 10m and maximum wave heights close to 20m (and even greater) may occur. Such extreme storms, which in the past were noticed only once in four or five years, are more recent to be faced almost every year in the Black Sea, and this seems to be a consequence of the climate changes. The analysis performed included also the dynamics of the monthly and annual significant wave height maxima as well as the identification of the most probable spatial and temporal occurrences of the extreme storm events. Finally, it can be concluded that the present work provides valuable information related to the characteristics of the storm conditions and on their dynamics in the Black Sea. This environment is currently subjected to high navigation traffic and intense offshore and nearshore activities and the strong storms that systematically occur may produce accidents with very serious consequences.

Keywords: Black Sea, extreme storms, SWAN simulations, waves

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Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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Rapid urbanization significantly change land use, urban nature, land surface vegetation cover, and heat distribution, leading to the formation of urban heat island (UHI) effect and affecting the healthy growth of cities and the comfort of human living style. Past information and present changes in Land Surface Temperature (LST) and urban landscapes could be useful to geographers, environmentalists, and urban planners in an attempt to shape the urban development process and mitigate the effects of urban heat islands (UHI). This study aims at using Satellite Remote Sensing (SRS) and GIS techniques to develop an approach for assessing the urban nature and UHI effects in Lahore, Pakistan. The study employed the Radiative Transfer Method (RTM) in estimating LST to assess the SUHI effect during the interval of 20 years (2000-2020). The assessment was performed by the available Landsat 7/ETM+ and Landsat 8/OIL_TIRs data for the years 2000, 2010, and 2020 respectively. Pearson’s correlation and normalized mutual information were applied to investigate the relationship between green space characteristics and LST. The result of this work revealed that the influence of urban heat island is not always at the city centers but sometimes in the outskirt where a lot of development activities were going on towards the direction of expansion of Lahore, Pakistan. The present study explores the usage of image processing and spatial analysis in the drive towards achieving urban greening of Lahore and a sustainable urban environment in terms of urban planning, policy, and decision making and promoting the healthy and sustainable urban environment of the city.

Keywords: urban nature, urban heat islands, urban green space, land use, Lahore

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Authors: Oladejo Olagoke Peter, Adagunodo T. A., Ogunkoya C. O.

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The research investigated the arrangement of some geological features under Ilesa employing aeromagnetic data. The obtained data was subjected to various data filtering and processing techniques, which are Total Horizontal Derivative (THD), Depth Continuation and Analytical Signal Amplitude using Geosoft Oasis Montaj 6.4.2 software. The Reduced to the Equator –Total Magnetic Intensity (TRE-TMI) outcomes reveal significant magnetic anomalies, with high magnitude (55.1 to 155 nT) predominantly at the Northwest half of the area. Intermediate magnetic susceptibility, ranging between 6.0 to 55.1 nT, dominates the eastern part, separated by depressions and uplifts. The southern part of the area exhibits a magnetic field of low intensity, ranging from -76.6 to 6.0 nT. The lineaments exhibit varying lengths ranging from 2.5 and 16.0 km. Analyzing the Rose Diagram and the analytical signal amplitude indicates structural styles mainly of E-W and NE-SW orientations, particularly evident in the western, SW and NE regions with an amplitude of 0.0318nT/m. The identified faults in the area demonstrate orientations of NNW-SSE, NNE-SSW and WNW-ESE, situated at depths ranging from 500 to 750 m. Considering the divergence magnetic susceptibility, structural style or orientation of the lineaments, identified fault and their depth, these lithological features could serve as a valuable foundation for assessing ground motion, particularly in the presence of sufficient seismic energy.

Keywords: lineament, aeromagnetic, anomaly, fault, magnetic

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Authors: Raphael Palucci Rosa, Giuseppe Rosace

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Stereolithography (SLA) is one of the 3D-printing technologies that has been steadily growing in popularity for both industrial and personal applications due to its versatility, high accuracy, and low cost. Its printing process consists of using a light emitter to solidify photosensitive liquid resins layer-by-layer to produce solid objects. However, the majority of the resins used in SLA are derived from petroleum and characterized by toxicity, stability, and recalcitrance to degradation in natural environments. Aiming to develop an eco-friendly resin, in this work, different combinations of a standard commercial SLA resin (Peopoly UV professional) with a vegetable-based resin were investigated. To reach this goal, different mass concentrations (varying from 10 to 50 wt%) of acrylated epoxidized soybean oil (AESO), a vegetable resin produced from soyabean oil, were mixed with a commercial acrylate-based resin. 1.0 wt% of Diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide (TPO) was used as photo-initiator, and the samples were printed using a Peopoly moai 130. The machine was set to operate at standard configurations when printing commercial resins. After the print was finished, the excess resin was drained off, and the samples were washed in isopropanol and water to remove any non-reacted resin. Finally, the samples were post-cured for 30 min in a UV chamber. FT-IR analysis was used to confirm the UV polymerization of the formulated resin with different AESO/Peopoly ratios. The signals from 1643.7 to 1616, which corresponds to the C=C stretching of the AESO acrylic acids and Peopoly acrylic groups, significantly decreases after the reaction. The signal decrease indicates the consumption of the double bonds during the radical polymerization. Furthermore, the slight change of the C-O-C signal from 1186.1 to 1159.9 decrease of the signals at 809.5 and 983.1, which corresponds to unsaturated double bonds, are both proofs of the successful polymerization. Mechanical analyses showed a decrease of 50.44% on tensile strength when adding 10 wt% of AESO, but it was still in the same range as other commercial resins. The elongation of break increased by 24% with 10 wt% of AESO and swelling analysis showed that samples with a higher concentration of AESO mixed absorbed less water than their counterparts. Furthermore, high-resolution prototypes were printed using both resins, and visual analysis did not show any significant difference between both products. In conclusion, the AESO resin was successful incorporated into a commercial resin without affecting its printability. The bio-based resin showed lower tensile strength than the Peopoly resin due to network loosening, but it was still in the range of other commercial resins. The hybrid resin also showed better flexibility and water resistance than Peopoly resin without affecting its resolution. Finally, the development of new types of SLA resins is essential to provide new sustainable alternatives to the commercial petroleum-based ones.

Keywords: 3D-printing, bio-based, resin, soybean, stereolithography

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Authors: Nabil Jallouli, Luisa M. Pastrana-Martínez, Ana R. Ribeiro, Nuno F. F. Moreira, Joaquim L. Faria, Olfa Hentati, Adrián M. T. Silva, Mohamed Ksibi

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Degradation and mineralization of ibuprofen (IBU) were investigated using Ultraviolet (UV) Light Emitting Diodes (LEDs) in TiO2 photocatalysis. Samples of ultrapure water (UP) and a secondary treated effluent of a municipal wastewater treatment plant (WWTP), both spiked with IBU, as well as a highly concentrated IBU (230 mgL-1) pharmaceutical industry wastewater (PIWW), were tested in the TiO2/UV-LED system. Three operating parameters, namely, pH, catalyst load and number of LEDs were optimized. The process efficiency was evaluated in terms of IBU removal using high performance liquid chromatography (HPLC) and ultra-high performance liquid chromatography coupled to tandem mass spectrometry (UHPLC-MS/MS). Additionally, the mineralization was investigated by determining the dissolved organic carbon (DOC) content. The chemical structures of transformation products were proposed based on the data obtained using liquid chromatography with a high resolution mass spectrometer ion trap/time-of-flight (LC-MS-IT-TOF). A possible pathway of IBU degradation was accordingly proposed. Bioassays were performed using the marine bacterium Vibrio fischeri to evaluate the potential acute toxicity of original and treated wastewaters. TiO2 heterogeneous photocatalysis was efficient to remove IBU from UP and from PIWW, and less efficient in treating the wastewater from the municipal WWTP. The acute toxicity decreased by ca. 40% after treatment, regardless of the studied matrix.

Keywords: acute toxicity, Ibuprofen, UV-LEDs, wastewaters

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Authors: Seung Ho Park, Young Su Moon, Nam Ik Cho

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We propose a convolution neural network (CNN) for quality adaptive compression artifact reduction named QCARNet. The proposed method is different from the existing discriminative models that learn a specific model at a certain quality level. The method is composed of a quality estimation CNN (QECNN) and a compression artifact reduction CNN (CARCNN), which are two functionally separate CNNs. By connecting the QECNN and CARCNN, each CARCNN layer is able to adaptively reduce compression artifacts and preserve details depending on the estimated quality level map generated by the QECNN. We experimentally demonstrate that the proposed method achieves better performance compared to other state-of-the-art blind compression artifact reduction methods.

Keywords: compression artifact reduction, deblocking, image denoising, image restoration

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Authors: Oliveira M., Gonçalves L., Francisco I., Caramelo F., Vale F., Sanz D., Domingues M., Lopes M., Moreia D., Lopes T., Santos T., Cardoso H.

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The ARTHUR project consists of a platform that allows the virtual performance of maxillofacial surgeries, offering, in a photorealistic concept, the possibility for the patient to have an idea of the surgical changes before they are performed on their face. For this, the system brings together several image formats, dicoms and objs that, after loading, will generate the bone volume, soft tissues and hard tissues. The system also incorporates the patient's stereophotogrammetry, in addition to their data and clinical history. After loading and inserting data, the clinician can virtually perform the surgical operation and present the final result to the patient, generating a new facial surface that contemplates the changes made in the bone and tissues of the maxillary area. This tool acts in different situations that require facial reconstruction, however this project focuses specifically on two types of use cases: bone congenital disfigurement and acquired disfiguration such as oral cancer with bone attainment. Being developed a cloud based solution, with mobile support, the tool aims to reduce the decision time window of patient. Because the current simulations are not realistic or, if realistic, need time due to the need of building plaster models, patient rates on decision, rely on a long time window (1,2 months), because they don’t identify themselves with the presented surgical outcome. On the other hand, this planning was performed time based on average estimated values of the position of the maxilla and mandible. The team was based on averages of the facial measurements of the population, without specifying racial variability, so the proposed solution was not adjusted to the real individual physiognomic needs.

Keywords: 3D computing, image processing, image registry, image reconstruction

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Authors: Daniel Phifer, Anna Prokhodtseva

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DualBeam (FIB-SEM) has long been the technology of choice to sub-sample and characterize materials at site-specific locations which are difficult or impossible to extract by conventional embedding/polishing methods. Whereas Ga based FIB provides excellent resolution and enables precise material removal, the current is usually limited and only allows the extraction of small material biopsies typically ranging from 5-70um wide. Xe Plasma FIB, by contrast, has around 38x more current and can remove more material at the same time to extract significant sized chunks (100-1000um) of materials for further analysis. This increased volume has enabled time-prohibitive investigations like large grain 3D serial sectioning and EBSD and micro-machining for micro-mechanical testing. Investigation of the pore spaces with 3D modeling can determine the relative characteristics of the materials to help design or select properties for best function. Pore spaces can be described with a tortuosity number which is calculated by modules in the 3D analysis software. Xe Plasma FIB technology provides a workflow with sufficient volume to characterize porosity when both large-volume 3D materials characterization and nanometer resolution is required to understand the system.

Keywords: dual-beam, FIB-SEM, porosity, SOFC, solid oxide fuel cell

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Thomas Rockstuhl, Soon Ang, Kok Yee Ng, Linn Van Dyne

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Intercultural interactions are often challenging and fraught with conflicts. To shed light on how to interact effectively across cultures, academics and practitioners alike have advanced a plethora of intercultural competence models. However, the majority of this work has emphasized distal outcomes, such as job performance and cultural adjustment, rather than proximal outcomes, such as how individuals resolve inevitable intercultural conflicts. As a consequence, the processes by which individuals negotiate challenging intercultural conflicts are not well understood. The current study advances theorizing on intercultural conflict resolution by exploring antecedents of how people resolve intercultural conflicts. To this end, we examine creativity – the generation of novel and useful ideas – in the context of resolving cultural conflicts in intercultural interactions. Based on the dual-identity theory of creativity, we propose that individuals with greater international experience will display greater creativity and that the relationship is accentuated by individual’s cultural intelligence. Two studies test these hypotheses. The first study comprises 84 senior university students, drawn from an international organizational behavior course. The second study replicates findings from the first study in a sample of 89 executives from eleven countries. Participants in both studies provided protocols of their strategies for resolving two intercultural conflicts, as depicted in two multimedia-vignettes of challenging intercultural work-related interactions. Two research assistants, trained in intercultural management but blind to the study hypotheses, coded all strategies for their novelty and usefulness following scoring procedures for creativity tasks. Participants also completed online surveys of demographic background information, including their international experience, and cultural intelligence. Hierarchical linear modeling showed that surprisingly, while international experience is positively associated with usefulness, it is unrelated to novelty. Further, a person’s cultural intelligence strengthens the positive effect of international experience on usefulness and mitigates the effect of international experience on novelty. Theoretically, our findings offer an important theoretical extension to the dual-identity theory of creativity by identifying cultural intelligence as an important individual difference moderator that qualifies the relationship between international experience and creative conflict resolution. In terms of novelty, individuals higher in cultural intelligence seem less susceptible to rigidity effects of international experiences. Perhaps they are more capable of assessing which aspects of culture are relevant and apply relevant experiences when they brainstorm novel ideas. For utility, individuals high in cultural intelligence are better able to leverage on their international experience to assess the viability of their ideas because their richer and more organized cultural knowledge structure allows them to assess possible options more efficiently and accurately. In sum, our findings suggest that cultural intelligence is an important and promising intercultural competence that fosters creative resolutions to intercultural conflicts. We hope that our findings stimulate future research on creativity and conflict resolution in intercultural contexts.

Keywords: cultural Intelligence, intercultural conflict, intercultural creativity, international experience

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Authors: Mahesh Kumar Jat, Manisha Choudhary

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Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) have been used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: remote sensing, GIS, object based, classification

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Authors: Masood Hussain, Erol Pehlivan, Ahmet Avci, Ecem Guder

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Green synthesis of silver nanoparticles (AgNPs) was carried out by using echinacea flower extract as reducing/protecting agent. The effects of various operating parameters and additives on the dimensions such as stirring rate, temperature, pH of the solution, the amount of extract and concentration of silver nitrate were optimized in order to achieve monodispersed spherical and small size echinacea protected silver nanoparticles (echinacea-AgNPs) through biosynthetic method. The surface roughness and topography of synthesized metal nanoparticles were confirmed by using Atomic Force Microscopy (AFM). High-Resolution Transmission Electron Microscopic (HRTEM) results elaborated the formation of uniformly distributed Echinacea protected AgNPs (Echinacea-AgNPs) having an average size of 30.2±2nm.

Keywords: Echinacea flower extract, green synthesis, silver nanoparticles, morphology

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Authors: Mansa Radhakrishnan, Anwar Ali, Muhammad Rizwan Mughal

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Many universities around the world are working on modular and low budget architecture of small spacecraft to reduce the development cost of the overall system. This paper focuses on the design of a modular solar power harvesting system for a hexagonal-shaped small satellite. The designed solar power harvesting systems are composed of solar panels and power converter subsystems. The solar panel is composed of solar cells mounted on the external face of the printed circuit board (PCB), while the electronic components of power conversion are mounted on the interior side of the same PCB. The solar panel with dimensions 16.5cm × 99cm is composed of 36 solar cells (each solar cell is 4cm × 7cm) divided into four parallel banks where each bank consists of 9 solar cells. The output voltage of a single solar cell is 2.14V, and the combined output voltage of 9 series connected solar cells is around 19.3V. The output voltage of the solar panel is boosted to the satellite power distribution bus voltage level (28V) by a boost converter working on a constant voltage maximum power point tracking (MPPT) technique. The solar panel module is an eight-layer PCB having embedded coil in 4 internal layers. This coil is used to control the attitude of the spacecraft, which consumes power to generate a magnetic field and rotate the spacecraft. As power converter and distribution subsystem components are mounted on the PCB internal layer, therefore it is mandatory to do thermal analysis in order to ensure that the overall module temperature is within thermal safety limits. The main focus of the overall design is on compactness, miniaturization, and efficiency enhancement.

Keywords: small satellites, power subsystem, efficiency, MPPT

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Authors: Sang Yeong Choi, Woo Sung Park

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This paper presents the architecture design of the robot operability assessment simulation testbed (called "ROAST") for the resolution of robot operability problems occurred during interactions between human operators and robots. The basic idea of the ROAST architecture design is to enable the easy composition of legacy or new simulation models according to its purpose. ROAST architecture is based on IEEE1516 High Level Architecture (HLA) of defense modeling and simulation. The ROAST architecture is expected to provide the foundation framework for the easy construction of a simulation testbed to order to assess the robot operability during the robotic system design. Some of ROAST implementations and its usefulness are demonstrated through a simple illustrative example.

Keywords: robotic system, modeling and simulation, simulation architecture, operability assessment

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Authors: Habib Alah Dadgar, Nasim Norouzbeigi

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The precise definition margin of high and low-grade gliomas is crucial for treatment. We aimed to assess the feasibility of assessment of the resection legions with post-operative positron emission tomography (PET) using [18F]O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET). Four patients with the suspicion of high and low-grade were enrolled. Patients underwent post-operative [18F]FET-PET, pre-operative magnetic resonance imaging (MRI) and CT for clinical evaluations. In our study, three patients had negative response to recurrence and progression and one patient indicated positive response after surgery. [18F]FET-PET revealed a legion of increased radiotracer uptake in the dura in the craniotomy site for patient 1. Corresponding to the patient history, the study was negative for recurrence of brain tumor. For patient 2, there was a lesion in the right parieto-temporal with slightly increased uptake in its posterior part with SUVmax = 3.79, so the study was negative for recurrence evaluation. In patient 3 there was no abnormal uptake with negative result for recurrence of brain tumor. Intense radiotracer uptake in the left parietal lobe where in the MRI there was a lesion with no change in enhancement in the post-contrast image is indicated in patient 4. Assessment of the resection legions in high and low-grade gliomas with [18F]FET-PET seems to be useful.

Keywords: FET-PET, CT, glioma, MRI

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Authors: H. Ali, A. Whitehead

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Providing a panoramic view of famous landmarks around the world offers artistic and historic value for historians, tourists, and researchers. Exploring the history of famous landmarks by presenting a comprehensive view of a temporal panorama merged with geographical and historical information presents a unique challenge of dealing with images that span a long period, from the 1800’s up to the present. This work presents the concept of temporal panorama through a timeline display of aligned historic and modern images for many famous landmarks. Utilization of this panorama requires a collection of hundreds of thousands of landmark images from the Internet comprised of historic images and modern images of the digital age. These images have to be classified for subset selection to keep the more suitable images that chronologically document a landmark’s history. Processing of historic images captured using older analog technology under various different capturing conditions represents a big challenge when they have to be used with modern digital images. Successful processing of historic images to prepare them for next steps of temporal panorama creation represents an active contribution in cultural heritage preservation through the fulfillment of one of UNESCO goals in preservation and displaying famous worldwide landmarks.

Keywords: cultural heritage, image registration, image subset selection, registered image similarity, temporal panorama, timescapes

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Authors: Somojit Saha, Rohit K. Chatterjee, Sarit K. Das, Avijit Kar

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A new force field is designed for propagation of the parametric contour into deep narrow cortical fold in the application of knowledge based reconstruction of cerebral cortex from MR image of brain. Designing of this force field is highly inspired by the Generalized Gradient Vector Flow (GGVF) model and markedly differs in manipulation of image information in order to determine the direction of propagation of the contour. While GGVF uses edge map as its main driving force, the newly designed force field uses the map of distance between zero valued pixels and their nearest non-zero valued pixel as its main driving force. Hence, it is called Zero-Non-Zero Distance (ZNZD) force field. The objective of this force field is forceful propagation of the contour beyond spurious convergence due to partial volume effect (PVE) in to narrow sulcal fold. Being function of the corresponding non-zero pixel value, the force field has got an inherent property to determine spuriousness of the edge automatically. It is effectively applied along with some morphological processing in the application of cortical reconstruction to breach the hindrance of PVE in narrow sulci where conventional GGVF fails.

Keywords: deformable model, external force field, partial volume effect, cortical reconstruction, MR image of brain

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Khalid. M. O. Elmabrok, M. L. Burby, G. G. Nasr

Abstract:

Flow instability during gas lift operation is caused by three major phenomena – the density wave oscillation, the casing heading pressure and the flow perturbation within the two-phase flow region. This paper focuses on the causes and the effect of flow instability during gas lift operation and suggests ways to control it in order to maximise productivity during gas lift operations. A laboratory-scale two-phase flow system to study the effects of flow perturbation was designed and built. The apparatus is comprised of a 2 m long by 66 mm ID transparent PVC pipe with air injection point situated at 0.1 m above the base of the pipe. This is the point where stabilised bubbles were visibly clear after injection. Air is injected into the water filled transparent pipe at different flow rates and pressures. The behavior of the different sizes of the bubbles generated within the two-phase region was captured using a digital camera and the images were analysed using the advanced image processing package. It was observed that the average maximum bubbles sizes increased with the increase in the length of the vertical pipe column from 29.72 to 47 mm. The increase in air injection pressure from 0.5 to 3 bars increased the bubble sizes from 29.72 mm to 44.17 mm and then decreasing when the pressure reaches 4 bars. It was observed that at higher bubble velocity of 6.7 m/s, larger diameter bubbles coalesce and burst due to high agitation and collision with each other. This collapse of the bubbles causes pressure drop and reverse flow within two phase flow and is the main cause of the flow instability phenomena.

Keywords: gas lift instability, bubbles forming, bubbles collapsing, image processing

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Authors: Mohan Singh Mehata, R. K. Ratnesh

Abstract:

CdSe, CdSe/ZnS, and CdSe/CdS core-shell quantum dots (QDs) of 3-4 nm were developed by using chemical route and following successive ion layer adsorption and reaction (SILAR) methods. The prepared QDs have been examined by using X-ray diffraction, high-resolution electron microscopy and optical spectroscopy. The photoluminescence (PL) quantum yield (QY) of core-shell QDs increases with respect to the core, indicating that the radiative rate increases by the formation of shell around core, as evident by the measurement of PL lifetime. Further, the PL of bovine serum albumin is quenched strongly by the presence of core-shall QDs and follow the Stern-Volmer (S-V) relation, whereas the lifetime does not follow the S-V relation, demonstrating that the observed quenching is predominantly static in nature. Among all the QDs, the CdSe/ZnS QDs shows the least cytotoxicity hence most biocompatibility.

Keywords: biocompatibility, core-shell quantum dots, photoluminescence and lifetime, sensing ability

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Authors: Z. Ghorannevis, E. Akbarnejad, B. Aghazadeh, M. Ghoranneviss

Abstract:

Carbon nanotubes (CNTs) modified with semiconductor nanocrystalline particles may find wide applications due to their unique properties. Here Cadmium Sulfide (CdS) nanoparticles were successfully grown on Multi-Walled Carbon Nanotubes (MWNTs) via a magnetron sputtering method for the first time. The CdS/MWNTs sample was characterized with X-ray diffraction (XRD), Field Emission Scanning and High Resolution Transmission Electron Microscopies (SEM/TEM) and four point probe. The obtained images show clearly the decoration of the MWNTs by the CdS nanoparticles, and the XRD measurements indicate the CdS structure as hexagonal type. Moreover, the physical properties of the CdS/MWNTs were compared with the physical properties of the CdS nanoparticles grown on the silicon. Electrical measurements of CdS and CdS/MWNTs reveal that CdS/MWNTs has lower resistivity than the CdS sample which may be due to the higher carrier concentrations.

Keywords: CdS, MWNTs, HRTEM, magnetron sputtering

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Authors: Sethu Lekshmi, Shahanas, Prettha P.

Abstract:

All existing protocols in wireless networks are mainly based on Carrier Sense Multiple Access with Collision avoidance. By applying collision detection in wireless networks, the time spent on collision can be reduced and thus improves system throughput. However in a real WLAN scenario due to the use of nonlinear modulation techniques only receiver can decided whether a packet loss take place, even there are multiple transmissions. In this proposed method, the receiver or Access Point detects the collision when multiple data packets are transmitted from different wireless stations. Whenever the receiver detects a collision, it transmits a jamming signal to all the transmitting stations so that they can immediately stop their on-going transmissions. We also provide preferential access to all collided packet to reduce unfairness and to increase system throughput by reducing contention. However, this preferential access will not block the channel for the long time. Here, an in-band transmission is considered in which both the data frames and control frames are transmitted in the same channel. We also provide a simple mathematical model for the proposed protocol and give the simulation result of WLAN scenario under various capture thresholds.

Keywords: 802.11, WLAN, capture effect, collision detection, collision resolution, receiver initiated

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Authors: Gulfam Haider, sana danish

Abstract:

Convolutional Neural Networks (CNNs) have emerged as powerful tools for image classification, and the choice of optimizers profoundly affects their performance. The study of optimizers and their adaptations remains a topic of significant importance in machine learning research. While numerous studies have explored and advocated for various optimizers, the efficacy of these optimization techniques is still subject to scrutiny. This work aims to address the challenges surrounding the effectiveness of optimizers by conducting a comprehensive analysis and evaluation. The primary focus of this investigation lies in examining the performance of different optimizers when employed in conjunction with the popular activation function, Rectified Linear Unit (ReLU). By incorporating ReLU, known for its favorable properties in prior research, the aim is to bolster the effectiveness of the optimizers under scrutiny. Specifically, we evaluate the adjustment of these optimizers with both the original Softmax activation function and the modified ReLU activation function, carefully assessing their impact on overall performance. To achieve this, a series of experiments are conducted using a well-established benchmark dataset for image classification tasks, namely the Canadian Institute for Advanced Research dataset (CIFAR-10). The selected optimizers for investigation encompass a range of prominent algorithms, including Adam, Root Mean Squared Propagation (RMSprop), Adaptive Learning Rate Method (Adadelta), Adaptive Gradient Algorithm (Adagrad), and Stochastic Gradient Descent (SGD). The performance analysis encompasses a comprehensive evaluation of the classification accuracy, convergence speed, and robustness of the CNN models trained with each optimizer. Through rigorous experimentation and meticulous assessment, we discern the strengths and weaknesses of the different optimization techniques, providing valuable insights into their suitability for image classification tasks. By conducting this in-depth study, we contribute to the existing body of knowledge surrounding optimizers in CNNs, shedding light on their performance characteristics for image classification. The findings gleaned from this research serve to guide researchers and practitioners in making informed decisions when selecting optimizers and activation functions, thus advancing the state-of-the-art in the field of image classification with convolutional neural networks.

Keywords: deep neural network, optimizers, RMsprop, ReLU, stochastic gradient descent

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Authors: Matthias Banholzer, Hagen Müller, Michael Pfitzner

Abstract:

Gas internal combustion engines are widely used as propulsion systems or in power plants to generate heat and electricity. While there are different types of injection methods including the manifold port fuel injection and the direct injection, the latter has more potential to increase the specific power by avoiding air displacement in the intake and to reduce combustion anomalies such as backfire or pre-ignition. During the opening process of the injector, multiple flow regimes occur: subsonic, transonic and supersonic. To cover the wide range of Mach numbers a compressible pressure-based solver is used. While the standard Pressure Implicit with Splitting of Operators (PISO) method is used for the coupling between velocity and pressure, a high-resolution non-oscillatory central scheme established by Kurganov and Tadmor calculates the convective fluxes. A blending function based on the local Mach- and CFL-number switches between the compressible and incompressible regimes of the developed model. As the considered operating points are well above the critical state of the used fluids, the ideal gas assumption is not valid anymore. For the real gas thermodynamics, the models based on the Soave-Redlich-Kwong equation of state were implemented. The caloric properties are corrected using a departure formalism, for the viscosity and the thermal conductivity the empirical correlation of Chung is used. For the injector geometry, the dimensions of a diesel injector were adapted. Simulations were performed using different nozzle and needle geometries and opening curves. It can be clearly seen that there is a significant influence of all three parameters.

Keywords: high pressure gas injection, hybrid solver, hydrogen injection, needle opening process, real-gas thermodynamics

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Authors: Farhan Beg

Abstract:

A space vector based pulse width modulation control technique for the three-phase PWM converter is proposed in this paper. The proposed control scheme is based on a synchronous reference frame model. High performance and efficiency is obtained with regards to the DC bus voltage and the power factor considerations of the PWM rectifier thus leading to low losses. MATLAB/SIMULINK are used as a platform for the simulations and a SIMULINK model is presented in the paper. The results show that the proposed model demonstrates better performance and properties compared to the traditional SPWM method and the method improves the dynamic performance of the closed loop drastically. For the space vector based pulse width modulation, sine signal is the reference waveform and triangle waveform is the carrier waveform. When the value of sine signal is larger than triangle signal, the pulse will start producing to high; and then when the triangular signals higher than sine signal, the pulse will come to low. SPWM output will change by changing the value of the modulation index and frequency used in this system to produce more pulse width. When more pulse width is produced, the output voltage will have lower harmonics contents and the resolution will increase.

Keywords: power factor, SVPWM, PWM rectifier, SPWM

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Authors: Yanli Qi, Ning Lv, Jing Li

Abstract:

Sub-Nyquist sampling jamming method (SNSJ) is a well known deception jamming method for inverse synthetic aperture radar (ISAR). However, the anti-decoy of the SNSJ method performs easier since the amplitude of the false-target images are weaker than the real-target image; the false-target images always lag behind the real-target image, and all targets are located in the same cross-range. In order to overcome the drawbacks mentioned above, a simple modulation based on SNSJ (M-SNSJ) is presented in this paper. The method first uses amplitude modulation factor to make the amplitude of the false-target images consistent with the real-target image, then uses the down-range modulation factor and cross-range modulation factor to make the false-target images move freely in down-range and cross-range, respectively, thus the capacity of deception is improved. Finally, the simulation results on the six available combinations of three modulation factors are given to illustrate our conclusion.

Keywords: inverse synthetic aperture radar (ISAR), deceptive jamming, Sub-Nyquist sampling jamming method (SNSJ), modulation based on Sub-Nyquist sampling jamming method (M-SNSJ)

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Authors: Nowbuth Manta Devi, Rasmally Mohammed Hussein

Abstract:

Flood is one of the most devastating climate impacts that many countries are facing. Many different causes have been associated with the intensity of floods being recorded over time. Unplanned development, low carrying capacity of drains, clogged drains, construction in flood plains or increasing intensity of rainfall events. While a combination of these causes can certainly aggravate the flood conditions, in many cases, increasing drainage capacity has not reduced flood risk to the level that was expected. The present study analyzed the extent to which land use is contributing to aggravating impacts of flooding in a city. Satellite images have been analyzed over a period of 20 years at intervals of 5 years. Both unsupervised and supervised classification methods have been used with the image processing module of ArcGIS. The unsupervised classification was first compared to the basemap available in ArcGIS to get a first overview of the results. These results also aided in guiding data collection on-site for the supervised classification. The island of Mauritius is small, and there are large variations in land use over small areas, both within the built areas and in agricultural zones involving food crops. Larger plots of agricultural land under sugar cane plantations are relatively more easily identified. However, the growth stage and health of plants vary and this had to be verified during ground truthing. The results show that although there have been changes in land use as expected over a span of 20 years, this was not significant enough to cause a major increase in flood risk levels. A digital elevation model was analyzed for further understanding. It could not be noted that overtime, development tampered with natural flow paths in addition to increasing the impermeable areas. This situation results in backwater flows, hence increasing flood risks.

Keywords: climate change, flood, natural flow paths, small islands

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